Article(id=1236323802934735610, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236323797054312545, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202411240, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1732723200000, receivedDateStr=2024-11-28, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1772692164405, onlineDateStr=2026-03-05, pubDate=1758729600000, pubDateStr=2025-09-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772692164405, onlineIssueDateStr=2026-03-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772692164405, creator=13701087609, updateTime=1772692164405, updator=13701087609, issue=Issue{id=1236323797054312545, tenantId=1146029695717560320, journalId=1210938733613449225, year='2025', volume='54', issue='9', pageStart='1', pageEnd='178', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772692163003, creator=13701087609, updateTime=1772692223569, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1236324051153646111, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236323797054312545, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1236324051153646112, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236323797054312545, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=125, endPage=134, ext={EN=ArticleExt(id=1236323803282862854, articleId=1236323802934735610, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Application of automatic generation of chemical reactor networks in micro-mixing combustor, columnId=1211002405299294959, journalTitle=Thermal Power Generation, columnName=Thermal energy science research, runingTitle=null, highlight=null, articleAbstract=

Computational fluid dynamics-chemical reactor network (CFD-CRN) simulation is a suitable method for predicting NOx emissions from gas turbines. A universal CRN automatic partitioning/solving program was developed and then applied and verified on a natural gas micro-mixing combustor. Through analysis of flow and combustion characteristics in the micro-mixing combustor based on CFD simulation, CRN partitioning criteria are established: firstly, the air and fuel zones are extracted, then major zones along the axial direction are divided, and further the zones are subdivided radially/circumferentially according to fuel-staging locations. The results indicate that, the CRN automatic partitioning/solving program enhances generality by using an XML standardized information interface and is suitable for complex combustor structures. The relative error between the predicted and experimental NOx emissions under different operating conditions of the micro-mixing combustor is less than 11%, and the influence of CFD grid number on the NOx prediction by CRN is relatively small. The effect of fuel distribution ratio on NOx emissions from micro-mixing combustor is analyzed, and a suitable adjustment range is given. The proposed CRN automatic partitioning/solving algorithm has potential applications in predicting NOx emissions from gas turbines.

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计算流体力学-化学反应器网络(computational fluid dynamics-chemical reactor network,CFD-CRN)模拟是一种适合燃气轮机NOx排放预测的方法,基于此方法开发了具有通用性的CRN自动分区/求解程序,并在天然气微混燃烧室上进行应用与验证。通过CFD软件模拟分析微混燃烧室的流动和燃烧特性,建立CRN分区准则:首先将空气区和燃料区提取出来,然后沿轴向主分区,再根据燃料分级沿径向/周向细分区域。结果表明,CRN自动分区/求解程序使用可扩展标记语言XML(extensible markup language)规范化信息接口增强了通用性,适用于复杂燃烧室结构,对微混燃烧室不同工况的NOx排放预测值与实验值相对误差小于11%,并且CFD网格数对CRN预测NOx排放值的影响较小;同时分析了燃料分配比例对微混燃烧室NOx排放的影响,给出了合适的调节范围。该CRN自动分区/求解算法在燃气轮机NOx排放预测方面具有应用潜力。

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雷福林(1975),男,博士,研究员,主要研究方向为燃烧学、煤气化、多相流等,
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帅佳玮(2000),女,硕士研究生,主要研究方向为燃气轮机燃烧技术,

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Development of the heavy-duty gas turbine[J]. Thermal Turbine, 2012, 41(2): 83-88., articleTitle=Development of the heavy-duty gas turbine, refAbstract=null), Reference(id=1236323816700440867, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2021, volume=61, issue=12, pageStart=1423, pageEnd=1437, url=null, language=null, rfNumber=[2], rfOrder=2, authorNames=李苏辉, 张归华, 吴玉新, journalName=清华大学学报(自然科学版), refType=null, unstructuredReference=李苏辉, 张归华, 吴玉新. 面向未来燃气轮机的先进燃烧技术综述[J]. 清华大学学报(自然科学版), 2021, 61(12): 1423-1437., articleTitle=面向未来燃气轮机的先进燃烧技术综述, refAbstract=null), Reference(id=1236323816813687081, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2021, volume=61, issue=12, pageStart=1423, pageEnd=1437, url=null, language=null, rfNumber=[2], rfOrder=3, authorNames=LI Suhui, ZHANG Guihua, WU Yuxin, journalName=Journal of Tsinghua University (Science and Technology), refType=null, unstructuredReference=LI Suhui, ZHANG Guihua, WU Yuxin. Advanced combustion technologies for future gas turbines[J]. Journal of Tsinghua University (Science and Technology), 2021, 61(12): 1423-1437., articleTitle=Advanced combustion technologies for future gas turbines, refAbstract=null), Reference(id=1236323816914350382, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2020, volume=34, issue=9, pageStart=10459, pageEnd=10485, url=null, language=null, rfNumber=[3], rfOrder=4, authorNames=HAQUE M A, NEMITALLAH M A, ABDELHAFEZ A, journalName=Energy & Fuels, refType=null, unstructuredReference=HAQUE M A, NEMITALLAH M A, ABDELHAFEZ A, et al. Review of fuel/oxidizer-flexible combustion in gas turbines[J]. Energy & Fuels, 2020, 34(9): 10459-10485., articleTitle=Review of fuel/oxidizer-flexible combustion in gas turbines, refAbstract=null), Reference(id=1236323817090511156, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2019, volume=39, issue=1, pageStart=33, pageEnd=40, url=null, language=null, rfNumber=[4], rfOrder=5, authorNames=钱文凯, 朱民, 李苏辉, journalName=动力工程学报, refType=null, unstructuredReference=钱文凯, 朱民, 李苏辉, 等. 燃气轮机分级燃烧室NOx排放动力学模拟研究[J]. 动力工程学报, 2019, 39(1): 33-40., articleTitle=燃气轮机分级燃烧室NOx排放动力学模拟研究, refAbstract=null), Reference(id=1236323817220534584, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2019, volume=39, issue=1, pageStart=33, pageEnd=40, url=null, language=null, rfNumber=[4], rfOrder=6, authorNames=QIAN Wenkai, ZHU Min, LI Suhui, journalName=Journal of Chinese Society of Power Engineering, refType=null, unstructuredReference=QIAN Wenkai, ZHU Min, LI Suhui, et al. A kinetics study on NOx emission of an axially-staged gas turbine combustor[J]. Journal of Chinese Society of Power Engineering, 2019, 39(1): 33-40., articleTitle=A kinetics study on NOx emission of an axially-staged gas turbine combustor, refAbstract=null), Reference(id=1236323817342169404, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2023, volume=null, issue=null, pageStart=1, pageEnd=28, url=null, language=null, rfNumber=[5], rfOrder=7, authorNames=赵铁铮, journalName=null, refType=null, unstructuredReference=赵铁铮. 同轴分级天然气低排放燃烧室流动与燃烧特性研究[D]. 哈尔滨: 哈尔滨工程大学, 2023: 1-28., articleTitle=同轴分级天然气低排放燃烧室流动与燃烧特性研究, refAbstract=null), Reference(id=1236323817493164357, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2023, volume=null, issue=null, pageStart=1, pageEnd=28, url=null, language=null, rfNumber=[5], rfOrder=8, authorNames=ZHAO Tiezheng, journalName=null, refType=null, unstructuredReference=ZHAO Tiezheng. Study on flow and combustion characteristics of internally-staged natural gas low emission combustor[D]. Harbin: Harbin Engineering University, 2023: 1-28., articleTitle=Study on flow and combustion characteristics of internally-staged natural gas low emission combustor, refAbstract=null), Reference(id=1236323817618993482, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2009, volume=null, issue=null, pageStart=1, pageEnd=15, url=null, language=null, rfNumber=[6], rfOrder=9, authorNames=杨小龙, journalName=null, refType=null, unstructuredReference=杨小龙. 燃气轮机燃烧室化学反应器网络模型研究[D]. 北京: 中国科学院大学, 2009: 1-15., articleTitle=燃气轮机燃烧室化学反应器网络模型研究, refAbstract=null), Reference(id=1236323817728045391, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2009, volume=null, issue=null, pageStart=1, pageEnd=15, url=null, language=null, rfNumber=[6], rfOrder=10, authorNames=YANG Xiaolong, journalName=null, refType=null, unstructuredReference=YANG Xiaolong. The study of gas turbine combustor using chemical reactor network approach[D]. Beijing: University of Chinese Academy of Sciences, 2009: 1-15., articleTitle=The study of gas turbine combustor using chemical reactor network approach, refAbstract=null), Reference(id=1236323817824514383, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2018, volume=215, issue=null, pageStart=853, pageEnd=864, url=null, language=null, rfNumber=[7], rfOrder=11, authorNames=INNOCENTI A, ANDREINI A, BERTINI D, journalName=Fuel, refType=null, unstructuredReference=INNOCENTI A, ANDREINI A, BERTINI D, et al. Turbulent flow-field effects in a hybrid CFD-CRN model for the prediction of NOx and CO emissions in aero-engine combustors[J]. Fuel, 2018, 215: 853-864., articleTitle=Turbulent flow-field effects in a hybrid CFD-CRN model for the prediction of NOx and CO emissions in aero-engine combustors, refAbstract=null), Reference(id=1236323818042618197, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2002, volume=26, issue=9, pageStart=1171, pageEnd=1183, url=null, language=null, rfNumber=[8], rfOrder=12, authorNames=FALCITELLI M, PASINI S, TOGNOTTI L, journalName=Computers & Chemical Engineering, refType=null, unstructuredReference=FALCITELLI M, PASINI S, TOGNOTTI L. Modelling practical combustion systems and predicting NOx emissions with an integrated CFD based approach[J]. Computers & Chemical Engineering, 2002, 26(9): 1171-1183., articleTitle=Modelling practical combustion systems and predicting NOx emissions with an integrated CFD based approach, refAbstract=null), Reference(id=1236323819531596121, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2002, volume=174, issue=11/12, pageStart=27, pageEnd=42, url=null, language=null, rfNumber=[9], rfOrder=13, authorNames=FALCITELLI M, TOGNOTTI L, PASINI S, journalName=Combustion Science and Technology, refType=null, unstructuredReference=FALCITELLI M, TOGNOTTI L, PASINI S. An algorithm for extracting chemical reactor network models from CFD simulation of industrial combustion systems[J]. Combustion Science and Technology, 2002, 174(11/12): 27-42., articleTitle=An algorithm for extracting chemical reactor network models from CFD simulation of industrial combustion systems, refAbstract=null), Reference(id=1236323819644842334, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2021, volume=25, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[10], rfOrder=14, authorNames=KHODAYARI H, OMMI F, SABOOHI Z, journalName=Thermal Science and Engineering Progress, refType=null, unstructuredReference=KHODAYARI H, OMMI F, SABOOHI Z. Multiobjective optimization of a lean premixed laboratory combustor through CFD-CRN approach[J]. Thermal Science and Engineering Progress, 2021, 25: 101014., articleTitle=Multiobjective optimization of a lean premixed laboratory combustor through CFD-CRN approach, refAbstract=null), Reference(id=1236323819737117026, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2014, volume=28, issue=2, pageStart=1470, pageEnd=1488, url=null, language=null, rfNumber=[11], rfOrder=15, authorNames=MONAGHAN R F D, TAHIR R, BOURQUE G, journalName=Energy & Fuels, refType=null, unstructuredReference=MONAGHAN R F D, TAHIR R, BOURQUE G, et al. Detailed emissions prediction for a turbulent swirling nonpremixed flame[J]. Energy & Fuels, 2014, 28(2): 1470-1488., articleTitle=Detailed emissions prediction for a turbulent swirling nonpremixed flame, refAbstract=null), Reference(id=1236323819841974631, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2018, volume=null, issue=null, pageStart=37, pageEnd=54, url=null, language=null, rfNumber=[12], rfOrder=16, authorNames=SAMPAT R, journalName=null, refType=null, unstructuredReference=SAMPAT R. Automatic generation of chemical reactor networks for combustion simulations[D]. Delft: Delft University of Technology, 2018: 37-54., articleTitle=Automatic generation of chemical reactor networks for combustion simulations, refAbstract=null), Reference(id=1236323819984580974, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2023, volume=63, issue=4, pageStart=612, pageEnd=622, url=null, language=null, rfNumber=[13], rfOrder=17, authorNames=高桥东, 雷福林, 张哲巅, journalName=清华大学学报(自然科学版), refType=null, unstructuredReference=高桥东, 雷福林, 张哲巅. 预测NOx排放的化学反应器网络自动生成方法[J]. 清华大学学报(自然科学版), 2023, 63(4): 612-622., articleTitle=预测NOx排放的化学反应器网络自动生成方法, refAbstract=null), Reference(id=1236323820106215798, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2023, volume=63, issue=4, pageStart=612, pageEnd=622, url=null, language=null, rfNumber=[13], rfOrder=18, authorNames=GAO Qiaodong, LEI Fulin, ZHANG Zhedian, journalName=Journal of Tsinghua University (Science and Technology), refType=null, unstructuredReference=GAO Qiaodong, LEI Fulin, ZHANG Zhedian. Automatic generation method of a chemical reactor network for predicting NOx emissions[J]. Journal of Tsinghua University (Science and Technology), 2023, 63(4): 612-622., articleTitle=Automatic generation method of a chemical reactor network for predicting NOx emissions, refAbstract=null), Reference(id=1236323820211073401, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2019, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[14], rfOrder=19, authorNames=ZUBRILIN I A, GURAKOV N I, SEMENIKHIN A S, journalName=null, refType=null, unstructuredReference=ZUBRILIN I A, GURAKOV N I, SEMENIKHIN A S, et al. Simulation of CO emission in primary and secondary zone of a small gas turbine combustion chamber using CFD and reactors network[C]. ASME 2019 Gas Turbine India Conference. Chennai, Tamil Nadu: ASME, 2019., articleTitle=Simulation of CO emission in primary and secondary zone of a small gas turbine combustion chamber using CFD and reactors network, refAbstract=null), Reference(id=1236323820332708217, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2020, volume=16, issue=3, pageStart=29, pageEnd=33, url=null, language=null, rfNumber=[15], rfOrder=20, authorNames=张文瀚, 王国峰, 赵巧男, journalName=沈阳工程学院学报(自然科学版), refType=null, unstructuredReference=张文瀚, 王国峰, 赵巧男, 等. 基于CRN方法的空气分级燃烧室NOx排放研究[J]. 沈阳工程学院学报(自然科学版), 2020, 16(3): 29-33., articleTitle=基于CRN方法的空气分级燃烧室NOx排放研究, refAbstract=null), Reference(id=1236323820454343040, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2020, volume=16, issue=3, pageStart=29, pageEnd=33, url=null, language=null, rfNumber=[15], rfOrder=21, authorNames=ZHANG Wenhan, WANG Guofeng, ZHAO Qiaonan, journalName=Journal of Shenyang Institute of Engineering (National Science), refType=null, unstructuredReference=ZHANG Wenhan, WANG Guofeng, ZHAO Qiaonan, et al. Study on NOx emission of air staged combustion chamber based on CRN method[J]. Journal of Shenyang Institute of Engineering (National Science), 2020, 16(3): 29-33., articleTitle=Study on NOx emission of air staged combustion chamber based on CRN method, refAbstract=null), Reference(id=1236323820567589250, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2023, volume=63, issue=4, pageStart=660, pageEnd=669, url=null, language=null, rfNumber=[16], rfOrder=22, authorNames=田园, 耿俊杰, 孙逸凡, journalName=清华大学学报(自然科学版), refType=null, unstructuredReference=田园, 耿俊杰, 孙逸凡, 等. 天然气径向分级燃烧室低NOx排放的优化研究[J]. 清华大学学报(自然科学版), 2023, 63(4): 660-669., articleTitle=天然气径向分级燃烧室低NOx排放的优化研究, refAbstract=null), Reference(id=1236323820680835466, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2023, volume=63, issue=4, pageStart=660, pageEnd=669, url=null, language=null, rfNumber=[16], rfOrder=23, authorNames=TIAN Yuan, GENG Junjie, SUN Yifan, journalName=Journal of Tsinghua University (Science and Technology), refType=null, unstructuredReference=TIAN Yuan, GENG Junjie, SUN Yifan, et al. Optimization investigation of low NOx emissions of natural gas radially staged combustor[J]. Journal of Tsinghua University (Science and Technology), 2023, 63(4): 660-669., articleTitle=Optimization investigation of low NOx emissions of natural gas radially staged combustor, refAbstract=null), Reference(id=1236323820785693073, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2000, volume=null, issue=null, pageStart=111, pageEnd=143, url=null, language=null, rfNumber=[17], rfOrder=24, authorNames=TURNS S R, journalName=An introduction to combustion: concepts and applications, refType=null, unstructuredReference=TURNS S R. An introduction to combustion: concepts and applications[M]. 2nd ed. New York: McGraw Hill Education, 2000: 111-143., articleTitle=null, refAbstract=null), Reference(id=1236323820882162066, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2013, volume=27, issue=3, pageStart=1643, pageEnd=1651, url=null, language=null, rfNumber=[18], rfOrder=25, authorNames=PARK J, NGUYEN T H, JOUNG D, journalName=Energy & Fuels, refType=null, unstructuredReference=PARK J, NGUYEN T H, JOUNG D, et al. Prediction of NOx and CO emissions from an industrial lean-premixed gas turbine combustor using a chemical reactor network model[J]. Energy & Fuels, 2013, 27(3): 1643-1651., articleTitle=Prediction of NOx and CO emissions from an industrial lean-premixed gas turbine combustor using a chemical reactor network model, refAbstract=null), Reference(id=1236323820987019674, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2023, volume=43, issue=12, pageStart=4657, pageEnd=4669, url=null, language=null, rfNumber=[19], rfOrder=26, authorNames=耿俊杰, 田园, 孙逸凡, journalName=中国电机工程学报, refType=null, unstructuredReference=耿俊杰, 田园, 孙逸凡, 等. 基于化学反应器网络方法的燃气轮机燃烧室NOx排放研究[J]. 中国电机工程学报, 2023, 43(12): 4657-4669., articleTitle=基于化学反应器网络方法的燃气轮机燃烧室NOx排放研究, refAbstract=null), Reference(id=1236323821083488668, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, doi=null, pmid=null, pmcid=null, year=2023, volume=43, issue=12, pageStart=4657, pageEnd=4669, url=null, language=null, rfNumber=[19], rfOrder=27, authorNames=GENG Junjie, TIAN Yuan, SUN Yifan, journalName=Proceedings of the CSEE, refType=null, unstructuredReference=GENG Junjie, TIAN Yuan, SUN Yifan, et al. Investigation on NOx emission characteristics of gas turbine combustor based on chemical reactor network method[J]. 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journalId=1210938733613449225, articleId=1236323802934735610, language=EN, label=Fig.8, caption=Variations of predicted NOx mass concentration with proportion of second-stage fuel allocation at different first-stage fuel ratios, figureFileSmall=g4DyoPoftY34Ls6JU3ka/Q==, figureFileBig=SM7uIB917gpXzqsyl8exYA==, tableContent=null), ArticleFig(id=1236323813273694367, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=CN, label=图8, caption=不同第1级燃料占比下NOx预测值随第2级燃料分配比例的变化情况, figureFileSmall=g4DyoPoftY34Ls6JU3ka/Q==, figureFileBig=SM7uIB917gpXzqsyl8exYA==, tableContent=null), ArticleFig(id=1236323813399523498, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=EN, label=Tab.1, caption=

Main components of the fuel

, figureFileSmall=null, figureFileBig=null, tableContent=
成分CH4C2H6CO2N2CO
体积分数/%95.431.771.030.970.80
), ArticleFig(id=1236323813542129843, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=CN, label=表1, caption=

燃料主要成分

, figureFileSmall=null, figureFileBig=null, tableContent=
成分CH4C2H6CO2N2CO
体积分数/%95.431.771.030.970.80
), ArticleFig(id=1236323814997553338, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=EN, label=Tab.2, caption=

Working conditions

, figureFileSmall=null, figureFileBig=null, tableContent=
负荷L操作压力p/MPa空气温度/K燃料温度/K空气流量/(kg·s–1)一级燃料流量/(kg·s–1)二级燃料流量/(kg·s–1)三级燃料流量/(kg·s–1)
1.00.5977422831.3886.730×10–39.520×10–31.429×10–2
1.00.3127452830.6663.430×10–34.850×10–37.330×10–3
0.80.6247122831.6108.930×10–38.820×10–31.343×10–2
0.80.2997092830.7823.570×10–35.040×10–37.640×10–3
0.60.5966842831.6099.870×10–302.077×10–2
0.60.3116832830.7674.870×10–301.032×10–2
), ArticleFig(id=1236323815123382463, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=CN, label=表2, caption=

工况条件

, figureFileSmall=null, figureFileBig=null, tableContent=
负荷L操作压力p/MPa空气温度/K燃料温度/K空气流量/(kg·s–1)一级燃料流量/(kg·s–1)二级燃料流量/(kg·s–1)三级燃料流量/(kg·s–1)
1.00.5977422831.3886.730×10–39.520×10–31.429×10–2
1.00.3127452830.6663.430×10–34.850×10–37.330×10–3
0.80.6247122831.6108.930×10–38.820×10–31.343×10–2
0.80.2997092830.7823.570×10–35.040×10–37.640×10–3
0.60.5966842831.6099.870×10–302.077×10–2
0.60.3116832830.7674.870×10–301.032×10–2
), ArticleFig(id=1236323815232434374, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=EN, label=Tab.3, caption=

Critical temperatures for division of low-temperature zone near the wall under different operating conditions

, figureFileSmall=null, figureFileBig=null, tableContent=
工况临界温度值/K
L1.0_p 0.5971 200
L0.8_p 0.6241 200
L0.6_p 0.5961 200
L1.0_p 0.3121 350
L0.8_p 0.2991 200
L0.6_p 0.3111 150
), ArticleFig(id=1236323815341486287, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=CN, label=表3, caption=

不同工况近壁面低温区划分的临界温度值

, figureFileSmall=null, figureFileBig=null, tableContent=
工况临界温度值/K
L1.0_p 0.5971 200
L0.8_p 0.6241 200
L0.6_p 0.5961 200
L1.0_p 0.3121 350
L0.8_p 0.2991 200
L0.6_p 0.3111 150
), ArticleFig(id=1236323815442149590, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=EN, label=Tab.4, caption=

Effect of CFD grid number on CRN prediction of NOx emissions

, figureFileSmall=null, figureFileBig=null, tableContent=
网格数/万NOx质量浓度/(mg·m–3)
CRN预测值实验值
46029.4528.67
55532.7828.67
85731.5628.67
1 10032.3428.67
), ArticleFig(id=1236323815555395808, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=CN, label=表4, caption=

CFD网格数对CRN预测NOx排放的影响

, figureFileSmall=null, figureFileBig=null, tableContent=
网格数/万NOx质量浓度/(mg·m–3)
CRN预测值实验值
46029.4528.67
55532.7828.67
85731.5628.67
1 10032.3428.67
), ArticleFig(id=1236323815656059112, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=EN, label=Tab.5, caption=

Comparison between the predicted and experimental NOx values under different operating conditions

, figureFileSmall=null, figureFileBig=null, tableContent=
工况NOx质量浓度/(mg·m–3)相对误差/%
CRN预测值实验值
L1.0_p 0.59731.5628.6710.08
L0.8_p 0.62446.3945.611.71
L0.6_p 0.596161.76162.310.34
L1.0_p 0.31275.4177.522.72
L0.8_p 0.29931.9729.169.64
L0.6_p 0.311180.28179.130.64
), ArticleFig(id=1236323815836414192, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=CN, label=表5, caption=

不同工况的NOx预测值与实验值对比

, figureFileSmall=null, figureFileBig=null, tableContent=
工况NOx质量浓度/(mg·m–3)相对误差/%
CRN预测值实验值
L1.0_p 0.59731.5628.6710.08
L0.8_p 0.62446.3945.611.71
L0.6_p 0.596161.76162.310.34
L1.0_p 0.31275.4177.522.72
L0.8_p 0.29931.9729.169.64
L0.6_p 0.311180.28179.130.64
), ArticleFig(id=1236323815958049016, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=EN, label=Tab.6, caption=

Ranges of second-stage fuel ratio to keep NOx emission mass concentrations within the 41 mg/m3 at different first-stage fuel ratios

, figureFileSmall=null, figureFileBig=null, tableContent=
第一级燃料占比/%第二级燃料占比/%
15.827.6~38.5
19.024.6~38.6
22.222.0~38.4
25.422.0~37.2
28.026.6~30.0
28.6
), ArticleFig(id=1236323816062906622, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236323802934735610, language=CN, label=表6, caption=

不同第1级燃料占比下NOx排放质量浓度保持在41 mg/m3内的第2级燃料分配比例范围

, figureFileSmall=null, figureFileBig=null, tableContent=
第一级燃料占比/%第二级燃料占比/%
15.827.6~38.5
19.024.6~38.6
22.222.0~38.4
25.422.0~37.2
28.026.6~30.0
28.6
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化学反应器网络自动生成方法在微混燃烧室中的应用
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帅佳玮 1, 2 , 雷福林 1, 2 , 张哲巅 1, 2
热力发电 | 热能科学研究 2025,54(9): 125-134
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热力发电 | 热能科学研究 2025, 54(9): 125-134
化学反应器网络自动生成方法在微混燃烧室中的应用
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帅佳玮1, 2 , 雷福林1, 2 , 张哲巅1, 2
作者信息
  • 1.中国科学院先进能源动力重点实验室(工程热物理研究所),北京 100190
  • 2.中国科学院大学工程科学学院,北京 100049
  • 帅佳玮(2000),女,硕士研究生,主要研究方向为燃气轮机燃烧技术,

通讯作者:

雷福林(1975),男,博士,研究员,主要研究方向为燃烧学、煤气化、多相流等,
Application of automatic generation of chemical reactor networks in micro-mixing combustor
Jiawei SHUAI1, 2 , Fulin LEI1, 2 , Zhedian ZHANG1, 2
Affiliations
  • 1.Key Laboratory of Advanced Energy and Power, Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China
  • 2.School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
出版时间: 2025-09-25 doi: 10.19666/j.rlfd.202411240
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计算流体力学-化学反应器网络(computational fluid dynamics-chemical reactor network,CFD-CRN)模拟是一种适合燃气轮机NOx排放预测的方法,基于此方法开发了具有通用性的CRN自动分区/求解程序,并在天然气微混燃烧室上进行应用与验证。通过CFD软件模拟分析微混燃烧室的流动和燃烧特性,建立CRN分区准则:首先将空气区和燃料区提取出来,然后沿轴向主分区,再根据燃料分级沿径向/周向细分区域。结果表明,CRN自动分区/求解程序使用可扩展标记语言XML(extensible markup language)规范化信息接口增强了通用性,适用于复杂燃烧室结构,对微混燃烧室不同工况的NOx排放预测值与实验值相对误差小于11%,并且CFD网格数对CRN预测NOx排放值的影响较小;同时分析了燃料分配比例对微混燃烧室NOx排放的影响,给出了合适的调节范围。该CRN自动分区/求解算法在燃气轮机NOx排放预测方面具有应用潜力。

微混燃烧室  /  化学反应器网络  /  CRN分区算法  /  燃料分级  /  NOx排放

Computational fluid dynamics-chemical reactor network (CFD-CRN) simulation is a suitable method for predicting NOx emissions from gas turbines. A universal CRN automatic partitioning/solving program was developed and then applied and verified on a natural gas micro-mixing combustor. Through analysis of flow and combustion characteristics in the micro-mixing combustor based on CFD simulation, CRN partitioning criteria are established: firstly, the air and fuel zones are extracted, then major zones along the axial direction are divided, and further the zones are subdivided radially/circumferentially according to fuel-staging locations. The results indicate that, the CRN automatic partitioning/solving program enhances generality by using an XML standardized information interface and is suitable for complex combustor structures. The relative error between the predicted and experimental NOx emissions under different operating conditions of the micro-mixing combustor is less than 11%, and the influence of CFD grid number on the NOx prediction by CRN is relatively small. The effect of fuel distribution ratio on NOx emissions from micro-mixing combustor is analyzed, and a suitable adjustment range is given. The proposed CRN automatic partitioning/solving algorithm has potential applications in predicting NOx emissions from gas turbines.

micro-mixing combustor  /  chemical reactor network  /  CRN partitioning algorithm  /  fuel-staging  /  NOx emission
帅佳玮, 雷福林, 张哲巅. 化学反应器网络自动生成方法在微混燃烧室中的应用. 热力发电, 2025 , 54 (9) : 125 -134 . DOI: 10.19666/j.rlfd.202411240
Jiawei SHUAI, Fulin LEI, Zhedian ZHANG. Application of automatic generation of chemical reactor networks in micro-mixing combustor[J]. Thermal Power Generation, 2025 , 54 (9) : 125 -134 . DOI: 10.19666/j.rlfd.202411240
燃气轮机排放的污染物NOx受到环保法规的严格限制[1],因此需发展低污染燃烧技术,包括燃料/空气分级燃烧、微混燃烧、烟气回流及柔和燃烧(mild combustion)等[2-3]。燃气轮机在实际运行中会面对复杂多变的工况条件,如负荷变化、燃料/空气分配及种类差异、运行参数变动等,因此对NOx排放的精准预测显得尤为重要[4-5]。计算流体力学-化学反应器网络(computational fluid dynamics-chemical reactor network,CFD-CRN)模拟方法基于燃烧室CFD模拟的流场特征构建CRN模型,然后采用详细化学反应机理求解CRN模型得到污染物排放量,具有计算量较小,预测精度较高,并且可用于研究变参数对预测污染物排放的影响,得到广泛应用[6-7]。该方法目前已经实现基于数值算法自动化构建CRN模型,克服了传统经验性划分和人工分析燃烧室流场的局限性。
为了更好体现燃烧室的流动特征与化学反应过程,研究者们越来越注重对自动化分区算法的开发。Falcitelli等人[8-9]基于CFD模拟结果,依据温度与化学计量数对燃烧室初步划分,再根据混合不均匀性指数进行区域的合并与重组,旨在形成数量较少且内部均匀性强的区域,并在DSMOKE软件中求解CRN;该算法成功应用于电站锅炉,生成的CRN反应器数量近400个。Khodayari等人[10]则利用ENERGICO软件构建贫预混燃烧器的CRN模型,依据O2/CH4摩尔分数、轴向速度和混合比等参数进行区域划分,利用非线性温度间隔细化高温区域的划分,构建了含84个反应器的CRN模型,并通过CHEMKIN软件求解计算NOx排放值。Monaghan等人[11]使用C语言编码的Fluent软件用户定义函数(UDF),根据预先定义的温度和轴向速度等参数,将旋流非预混火焰划分为包含5 000多个PSR的CRN模型,并使用KPPSMOKE软件求解CRN预测NOx等污染物的排放。Sampat R[12]采用Python语言与广度优先搜索(BFS)算法自动化处理CFD模拟数据,将三维CFD体网格聚类成少数反应器,构建网络模型并在Cantera中求解计算。此过程基于预设相似性标准迭代进行,直至反应器数量达上限或NOx预测稳定;此算法应用于实验室尺度的燃烧器,构建了包含1 000个左右的反应器的CRN模型。高桥东等[13]采用Python编程语言开发了燃烧室CRN自动生成程序,引入几何结构、流场和温度场等特征参数,以自定义区域划分准则对体网格聚类进行区域划分,进而构建CRN模型,集成Cantera求解CRN预测NOx排放。该算法自动构建的CRN模型数量在几十个量级,结构清晰,可改变边界条件复用已构建CRN模型预测其他工况的NOx排放。
化学反应器网络方法也被应用于优化分级燃烧策略的研究。Zubrilin等人[14]在Chemkin软件中构建了包含1个PSR和1个PFR的CRN模型,用于模拟小型燃烧室一、二级区域,并用该模型分析不同区域的当量比对NOx排放的影响。张文瀚等[15]基于Chemkin软件构建了空气分级燃烧室不同工况的CRN模型,研究了空气分配比对NOx排放影响,发现减少一级空气的喷入量,可有效降低NOx排放。田园等[16]研究了天然气径向分级燃烧室低污染物排放的优化方法。燃烧室由1个中心区和1个环形区组成,结果表明,当单个环形区喷嘴的燃料量等于中心区燃料量时,燃烧室可达低NOx排放。
本文旨在开发一种适用于复杂燃烧室结构的CRN自动分区/求解程序,并应用于天然气微混燃烧室。对燃烧室进行CFD模拟,分析不同工况下微混燃烧室的流场特征和燃烧特性。基于CFD模拟数据,采用CRN自动分区/求解程序建立了微混燃烧室60%~100%负荷工况CRN模型,计算NOx排放,并与实验数据进行对比验证。此外,本文还探讨CFD网格数、不同级燃料分配比对预测NOx排放的影响。
本文研究对象为某型天然气燃气轮机环管型燃烧室的单筒燃烧室,其结构如图1所示。该低排放燃烧室使用微混燃烧喷嘴,微混喷嘴由45根管直径d为12 mm的微管组成,燃料与氧化剂首先在微管内强烈掺混,达到很高的混合程度进入燃烧室内燃烧。
该单筒燃烧室有1个空气入口和3个燃料入口,燃料分为三级,每级可以进行独立的调节与控制。第1级燃料通入中心10根微管,第2级燃料通入左右扇形区域的14根微管,第3级燃料通入上下扇形区域的21根微管。火焰筒上共有5圈气膜冷却孔和1圈掺混孔。掺混孔数量为10个,沿火焰筒周向均匀布置。
该单筒燃烧室有1个空气入口和3个燃料入口,燃料分为三级,每级可以进行独立的调节与控制。第1级燃料通入中心10根微管,第2级燃料通入左右扇形区域的14根微管,第3级燃料通入上下扇形区域的21根微管。火焰筒上共有5圈气膜冷却孔和1圈掺混孔。掺混孔数量为10个,沿火焰筒周向均匀布置。
在全温全压实验台上开展单筒微混燃烧室的燃烧特性实验。本研究选取微混燃烧室的6个实验工况作为模拟计算工况条件,包含0.3、0.6 MPa 2组不同的操作压力和60%、80%、100% 3种不同的工作负荷。在本文中,将这3种负荷工况分别简记为L0.6、L0.8、L1.0。实验使用天然气为燃料,以空气为氧化剂。对6组工况进行CFD模拟计算,构建CRN模型预测燃烧室出口NOx排放,并与实验结果进行对比验证。模拟计算用的天然气燃料成分以及工况条件分别如表1表2所示(均为标准状态下)。
使用ANSYS Fluent 2022 R1软件对燃烧室进行CFD模拟计算。采用多面体-六面体混合网格对微混燃烧室计算域进行网格划分,通过网格无关性分析选择网格数约为857万。湍流模型选用Realizable k-ε模型,近壁面流动选用可伸缩壁面函数(scalable wall functions)模拟;选用GRI-Mech 3.0燃烧反应机理耦合部分预混燃烧模型的火焰面生成流形(flamelet generated manifold,FGM)模型模拟燃烧过程,具体设置为非绝热的FGM模型,基于预混火焰面和进度变量空间(progress variable space)的火焰面求解方法。采用离散坐标(discrete ordinates,DO)辐射传热模型,流体吸收系数为wsggm-domain-based;压力速度耦合算法选用压力耦合方程组的半隐式(semi-implicit method for pressure linked equations,SIMPLE)算法,压力项和动量项松弛因子均为0.7,湍动能项和湍流耗散项松弛因子均为0.8,离散格式均设置为二阶。入口设置为质量流量边界条件,湍流强度为5%,出口设置为自由出流边界条件,壁面条件为标准无滑移绝热壁面。在计算过程中,能量方程收敛残差设置为10–6,其余参数收敛残差为10–3
文献[13]采用Python编程语言开发了CRN自动生成程序,但是在改变工况或划分标准时需要对程序进行修改,程序缺乏通用性。CRN自动生成方法分自动分区程序和求解程序2个程序模块。本文对CRN自动分区/求解程序进行改进以增强通用性,具体包括:使用可扩展标记语言(extensible markup language,XML)作为统一的数据存储标准,实现程序输入输出信息的规范化,便于修改,易于理解;所有工况参数和划分标准的修改都通过修改XML输入文件实现,无需修改程序,增强程序的通用性;开发简洁的CRN划分/求解程序的运行界面,操作简单,使用便捷。使用改进后的CRN自动分区/求解程序构建CRN模型进行NOx求解计算的基本流程如下。
1)使用ANSYS Fluent软件对燃烧室进行热态CFD模拟,旨在获取燃烧室内流场、温度场、组分场等关键特征信息。
2)导出CFD模拟数据,将需要用到的标量,如体网格ID、网格体积、三维坐标、压力、温度、组分含量等导出为CFD通用数据格式(CFD general notation system,CGNS)文件,并使用分层数据格式(hierarchical data format version 5,HDF5)保存算例和数据文件。
3)修改CRN自动分区程序的XML输入文件。其节点信息主要包括3个HDF5格式文件的存放路径、用到的物理量、流体域名称及ID、内部面、氧化剂入口面、燃料入口面、出口面的名称及ID、区域划分准则条件表达式、详细反应机理文件名、氧化剂和燃料的组分、温度、压力、初始当量比。流体域和各种面的名称及ID可以在ANSYS Fluent界面中查看。区域划分准则一般通过分析燃烧室几何、火焰结构、温度、组分含量及流动特性等确定。
4)运行CRN自动分区程序,在用户界面中选择XML输入文件,从CFD数据文件中筛选出流体域对应的数据,再根据区域划分准则对流体域数据进行处理。采用网格聚类算法,将符合特定划分标准的体网格聚类到同一个全混流反应器[17](perfectly stirred reactor,PSR)中,并依次执行各项分区准则,直至完成整个流体域的分区。分区完成后,程序计算各个反应器参数,如温度、压力和体积等,其中,反应器的体积为其所包含的各体网格体积之和;温度T和压力p则通过体积加权平均的方法计算得出。此外,程序还会计算得到各反应器间的质量流量以及进出口面的质量流量。最后,程序可将CRN分区结果存储为XML数据格式的文件,作为CRN求解程序的输入文件。
5)修改CRN求解程序的XML输入文件。其节点信息主要包括各反应器的体积、温度、压力和初始温度T0、反应器间的质量流量、进出口的质量流量及反应器连接关系、详细反应机理文件名、氧化剂和燃料的组分、温度、压力、初始当量比。可根据实际情况对CRN分区程序输出XML文件的某些参数进行适当调整,如修改反应器的初始温度T0和初始当量比。
6)运行CRN求解程序,在用户界面中选择XML输入文件,求解CRN达到稳定状态,得到NOx排放质量浓度。在求解程序中,为了保证各个反应器进出口的质量流量平衡,保持反应器出口的流量分配比例不变,根据实际输入质量流量校正各个反应器间的质量流量传递。CRN求解程序集成了开源反应动力学模拟软件Cantera,采用理想气体定压反应器来模拟PSR反应器,并使用质量流量控制器连接各反应器。程序将反应器参数以及反应器之间的连接关系依次赋值给各反应器,从而构建出完整的CRN模型。耦合详细化学反应机理求解CRN,获得各个反应器的温度、压力、体积、NOx质量浓度以及详细的组分信息,并将求解结果保存为XML文件,以便于后续分析。本研究中使用GRI-Mech 3.0详细化学反应机理。
在构建CRN时需要对燃烧室的流场、温度场、组分场等进行分析,确定合适的区域划分标准。图2为不同工况下微管出口截面的轴向速度分布。由图2可以看出,不同工况下的流场结构相似。在微混喷嘴之间存在一些回流区,但这些回流区相对较小,且分布较为均匀,因此在CRN区域划分时不单独划分回流区。中心点火器与喷嘴之间存在缝隙,有比较高的流速,应该将中心低温区域单独划分成一个CRN区域。火焰筒壁面与喷嘴之间也存在缝隙,因此,近壁面的低温区域也应该单独划分CRN区域。
图3为不同工况下微管出口截面CH4质量分数分布云图。从图3可以看出,每级微管出口的CH4质量分数分布比较均匀,这是因为空气从微管侧面对冲进入与燃料强烈掺混。微管出口流速很大,可以在火焰筒内进一步快速掺混,从而形成均匀的混合气,因而可以将每级的主燃烧区用PSR反应器来模拟。虽然在微管射流区域存在1个低温区,这会影响主燃烧区的体积,但对主燃烧区的温度基本没影响,因此本研究中不单独划分此低温区域。考虑到二、三级微管分别被分隔成两部分,因此在周向上将二、三级微管分别划分成2个CRN区域。负荷L=0.6的工况,只开了一、三级燃料,微管出口的甲烷质量分数更高,但还是可以在周向上将二、三级微管分别划分成2个CRN区域。因此在构建不同工况的CRN模型时,可以将燃料分级作为燃烧室区域划分的一个重要依据。
首先依据轴向位置坐标(气体流动方向),将燃烧室划分为空气区、燃料区、混合区、主燃烧区、掺混燃烧区、后火焰区等若干核心区域,如图4所示。然后根据燃料分级特点,将燃料区细化为3个子区域,混合区和主燃烧区在径/周向划分为5个子区域。
L1.0_p0.597工况为例,具体分区标准如下:
1)空气区选择氧气质量分数YO作为分区标准,以YO=0.232等值线为空气区的外沿。
YO0.232
2)燃料区根据几何结构参数和混合物分数f划分为三级。
(f0.999)((0.50949x0.48649)((0.48649x0.48049)(0.012r0.040)))
(f0.999)(0.48649x0.48049)(0.040 0r0.0848)(((z0)(0.3πrad1<0.1π))((z0)(0.1πrad1<0.3π)))
(f0.999)(0.48649x0.48049)(0.040 0r0.0848)(((y10)(0.4πrad2<0.4π))((y10)(0.2πrad2<0.2π)))
3)微混喷嘴燃料空气混合区包括5个子区域,第1级混合区域为靠近火焰筒中心的一圈微管,第2、3级混合区依据2、3级燃料的注入位置分别被划分为2个扇形区域。
(0.48049<x0.37849)(0.022r0.04)
(0.48049<x0.37849)(0.040<r0.078)((z0)(0.3πrad1<0.1π))
(0.48049x0.37849)(0.040r0.078)((z0)(0.1πrad1<0.3π))
(0.48049x0.37849)(0.040r0.078)((y10)(0.4πrad20.4π))
(0.48049x0.37849)(0.040r0.078)((y10)(0.2πrad20.2π))
4)采用温度为1 200 K等值线、轴向和径向坐标划分点火器对应的中心低温区和近火焰筒壁面的低温区。某些工况的温度等值线在1 150~1 350 K调整。
(x0.30)(0r0.022)
(x0.35)(r0.077)
(0.35<x0.30)(r0.071)(T1200)
5)主燃烧区按燃料分级划分为5个区域,采用几何参数进行划分。
(x0.30)(0.022<r0.04)
(x0.30)(z0)(0.3πrad10.1π)
(x0.30)(z0)(0.1πrad10.3π)
(x0.30)(y10)(0.4πrad2<0.4π)
(x0.30)(y10)(0.2πrad20.2π)
6)掺混燃烧区采用轴向坐标和温度为划分参数。采用温度为1 000、1 500、1 800 K等值线划分为4个区域。
(x0.20)(T1000)
(x0.20)(T1500)
(x0.20)(T1800)
(x0.20)(T1800)
7)后火焰区采用轴向坐标为划分参数。
x0.15
x0.10
x0.06
x0
其中,y1=y-0.456 66、r=y2+z22、rad1=tan–1(y1/z)、 rad2=tan–1(z /y1),xyzT分别代表体网格对应的三维坐标和温度。根据以上区域划分准则,构建了包含25个反应器的CRN模型。
在构建L=0.6工况的CRN模型时,选用的划分参数基本相同,主要差别在于左右扇形区域微管部分无燃料进入。因此在区域划分时,将这部分归于空气区,中心微管与上下扇形区域微管分别与第1级燃料、第3级燃料入口相连,具体表示如下。
1)燃料区
(f0.999)((0.50949x0.48649)((0.48649x0.48049)(0.012r0.040)))
(0.48649x0.48049)(0.040r0.0848)
2)混合区
(0.48049x0.37849)(0.022r0.04)
(0.48049x0.37849)(0.04r0.078)((y10)(0.4πrad20.4π))
(0.48049<x0.37849)(0.04<r0.078(y10)(0.2πrad20.2π)
其余区域的划分准则保持不变。依据此划分准则,构建包含22个反应器的CRN模型。表3列出了不同工况在划分近壁面低温区时的临界温度值。
尽管整体分区准则保持一致性,但各工况在划分近火焰筒壁面的低温区(式(12))时,采用了不同的临界温度值。这种差异是由于各工况进口参数不同,导致燃烧室内部的流动特征和火焰结构出现细微变化。
在采用CFD-CRN方法时,希望使用较少的CFD网格数量,构建的CRN依然能够获得较为准确的NOx预测结果。因此,有必要研究CFD网格数量对构建CRN预测NOx的影响。本研究选取L1.0_p0.597工况,分别采用了460万、555万、857万和1 100万的网格数进行CFD数值模拟计算,统计得到火焰筒内通过微管集合、气膜冷却孔及掺混孔的空气流量分配随网格数的变化趋势,如图5所示。其中,管束1、2、3分别代表第1圈10根微管、第2圈15根微管、第3圈20根微管集合。
图5可以看出,随着网格数的增加,不同位置的空气流量分配逐渐趋于稳定。当网格数增加到约857万时,各位置的空气流量分配基本不变,表明此时网格密度已经足够捕捉流场中的关键细节,再增加网格数对结果的改善有限,且会显著增加计算量。
基于不同网格数的CFD模拟结果,采用相同的区域划分标准来构建CRN模型,求解计算得到NOx排放结果见表4,其中所有NOx排放浓度都在标准状态下,干基、15%氧气体积分数。从表4可以看出,在不同网格数下CRN预测值与实验值均较为接近,预测最大误差为14.3%。随着网格数的增加,构建的CRN预测NOx质量浓度基本趋于稳定。由此可见,在利用CFD-CRN方法预测NOx质量浓度时,可以适当减少CFD网格数目,在减少计算量的同时,仍然可以实现对NOx质量浓度的精准预测。
针对表2中列出的6种工况,采用2.2节中的区域划分标准,使用CRN自动分区/求解程序构建相应的CRN模型,求解得到的NOx排放预测结果见表5。从表5可以看出,CRN模型预测的NOx质量浓度与实验值相比,误差均在11%以内,基本可以认为达到了对NOx的准确预测。
表5中显示各工况下排放NOx质量浓度变化很大,主要是因为燃料分级的当量比不同导致的。主燃烧区是主要的NOx生成区域[18],当量比高的主燃烧区NOx生成占比高。图6给出了不同燃料级对应的主燃烧区NOx生成量占总排放的比率。总体上,各种燃料分级情况下主燃烧区的总NOx生成量占总排放的90%以上。L0.8_p0.624工况的第1级主燃烧区的NOx生成量占80%左右,因为第1级的当量比比其他两级高很多。在分级当量比相同时,第1级主燃烧区的NOx生成速率更高一些,这是因为第2、3级主燃烧区受到壁面间隙和气膜冷却孔空气的影响更大,而第2、3级主燃烧区的NOx生成量与对应的微管数量基本成比例变化。尽管不同级的当量比存在差异,但总体上随着当量比的增加,燃烧火焰温度升高,NOx生成也呈现上升的趋势。
文献[13,19]研究表明CRN模板具有一定的工况适用范围,因为不同工况之间的流场存在相似性。基于这种相似性,在保持其他参数不变的情况下,仅调整入口燃料量,可以利用CRN模板对附近工况的NOx排放质量浓度进行预测。一般来讲,保持每个喷嘴的燃料量和空气量相同可以实现NOx生成量最小[16,19],但是有时为了避免燃烧振荡,需要调节燃料分级比例,使得每级微管的当量比有些差异。为此,以L0.8_p0.624工况为基准工况,调整不同级的燃料分配比例,并依据该工况对应的CRN模型预测燃料分配比例改变时的NOx排放情况,分析能够满足排放标准的变化范围,即在80%负荷时,NOx排放质量浓度在41 mg/m3以内。
首先,在保证稳定燃烧范围内,调整第1级燃料分配比例在15%~30%变化,其余两级燃料按照其包含的微管数量之比为2:3进行分配,得到CRN模型预测的NOx排放质量浓度变化曲线如图7所示。随着第1级燃料分配比例的增加,NOx排放量呈现先减后增的曲线特征。当第1级燃料分配比例在15.0%~28.2%时,NOx排放质量浓度能够保持在41 mg/m3排放限值以下,而当第1级燃料比例约为22.2%时为最佳比例,NOx生成量最小。当第1级燃料比例大于22.2%时,随该比例增加,当量比增加更快,促进了热力型NOx的快速提升;而当第1级燃料比例小于22.2%时,随该比例减小,第2、3级的当量比增加更慢,NOx的排放量增加更缓慢。
其次,在第1级燃料占比一定的情况下,深入分析第2级燃料分配比例变化对出口NOx质量浓度的影响,有助于进一步理解如何通过调整燃料分配比例来有效控制NOx的生成。在给定第1级燃料占比时,调整第2级燃料的分配比例在22.0%~40.0%变动,得到的NOx预测结果如图8所示,NOx排放质量浓度在41 mg/m3限值内的第2级燃料分配比的变化范围列于表6。从图8可以看出:NOx排放质量浓度随着第2级燃料分配比例的增加也呈现先减后增的曲线特征;且随着第1级燃料分配比例的增加,第2级燃料最佳分配比例点向左移动。
当第1级燃料比例较低时,其占比的增加会拓宽NOx排放达标的第2级燃料比例范围。当第1级燃料占比较高时,其占比的增加会缩小NOx排放达标的第2级燃料比例范围。特别是在第1级燃料占比大约超过28%时,无论如何调整第2级燃料分配比例,生成NOx质量浓度都基本维持在一个较高水平。第1级燃料占比处于15.8%~25.4%时,存在一个共同优化的第2级燃料占比区间,即27.6%~37.2%,在此区间内能够有效维持NOx的低排放水平。对应以上各级燃料占比区间,第1、2、3级微管的当量比变化范围分别为0.413~0.664、0.518~0.699、0.465~0.704。
本文采用CRN自动生成方法对天然气微混燃烧室不同工况下的NOx排放进行深入分析与预测。研究结果如下。
1)开发的CRN自动分区/求解程序使用XML数据格式规范化存储接口信息,具有通用性和灵活性,能够适用于复杂结构燃烧室的NOx排放预测。
2)利用CRN自动分区/求解程序构建6组工况的CRN模型能够较为准确预测微混燃烧室的NOx排放量,其与实验值相比的最大误差不超过11%。
3)基于不同网格数构建CRN模型对同一工况NOx预测结果基本一致,这表明在保证预测精度前提下,可以适当减少CFD网格数以提高计算效率。
4)分析了在80%负荷工况下第1、2级燃料分配比例对NOx排放的影响。当第1级燃料分配比例维持在15.8%~25.4%,第2级燃料分配比在27.6%~37.2%时,NOx排放质量浓度低于41 mg/m3
CRN自动分区/求解程序在预测复杂结构燃烧室NOx排放方面具有应用潜力与价值。然而,当前研究中区域划分标准主要聚焦于燃料分级的特点,并未对CRN划分准则进行深入研究,需要在后续的研究工作中进一步完善。
  • 国家科技重大专项(Y2019-I-0022-0021)
参考文献 引证文献
排序方式:
[1]
蒋洪德. 重型燃气轮机的现状和发展趋势[J]. 热力透平, 2012, 41(2): 83-88.
JIANG Hongde. Development of the heavy-duty gas turbine[J]. Thermal Turbine, 2012, 41(2): 83-88.
[2]
李苏辉, 张归华, 吴玉新. 面向未来燃气轮机的先进燃烧技术综述[J]. 清华大学学报(自然科学版), 2021, 61(12): 1423-1437.
LI Suhui, ZHANG Guihua, WU Yuxin. Advanced combustion technologies for future gas turbines[J]. Journal of Tsinghua University (Science and Technology), 2021, 61(12): 1423-1437.
[3]
HAQUE M A, NEMITALLAH M A, ABDELHAFEZ A, et al. Review of fuel/oxidizer-flexible combustion in gas turbines[J]. Energy & Fuels, 2020, 34(9): 10459-10485.
[4]
钱文凯, 朱民, 李苏辉, 等. 燃气轮机分级燃烧室NOx排放动力学模拟研究[J]. 动力工程学报, 2019, 39(1): 33-40.
QIAN Wenkai, ZHU Min, LI Suhui, et al. A kinetics study on NOx emission of an axially-staged gas turbine combustor[J]. Journal of Chinese Society of Power Engineering, 2019, 39(1): 33-40.
[5]
赵铁铮. 同轴分级天然气低排放燃烧室流动与燃烧特性研究[D]. 哈尔滨: 哈尔滨工程大学, 2023: 1-28.
ZHAO Tiezheng. Study on flow and combustion characteristics of internally-staged natural gas low emission combustor[D]. Harbin: Harbin Engineering University, 2023: 1-28.
[6]
杨小龙. 燃气轮机燃烧室化学反应器网络模型研究[D]. 北京: 中国科学院大学, 2009: 1-15.
YANG Xiaolong. The study of gas turbine combustor using chemical reactor network approach[D]. Beijing: University of Chinese Academy of Sciences, 2009: 1-15.
[7]
INNOCENTI A, ANDREINI A, BERTINI D, et al. Turbulent flow-field effects in a hybrid CFD-CRN model for the prediction of NOx and CO emissions in aero-engine combustors[J]. Fuel, 2018, 215: 853-864.
[8]
FALCITELLI M, PASINI S, TOGNOTTI L. Modelling practical combustion systems and predicting NOx emissions with an integrated CFD based approach[J]. Computers & Chemical Engineering, 2002, 26(9): 1171-1183.
[9]
FALCITELLI M, TOGNOTTI L, PASINI S. An algorithm for extracting chemical reactor network models from CFD simulation of industrial combustion systems[J]. Combustion Science and Technology, 2002, 174(11/12): 27-42.
[10]
KHODAYARI H, OMMI F, SABOOHI Z. Multiobjective optimization of a lean premixed laboratory combustor through CFD-CRN approach[J]. Thermal Science and Engineering Progress, 2021, 25: 101014.
[11]
MONAGHAN R F D, TAHIR R, BOURQUE G, et al. Detailed emissions prediction for a turbulent swirling nonpremixed flame[J]. Energy & Fuels, 2014, 28(2): 1470-1488.
[12]
SAMPAT R. Automatic generation of chemical reactor networks for combustion simulations[D]. Delft: Delft University of Technology, 2018: 37-54.
[13]
高桥东, 雷福林, 张哲巅. 预测NOx排放的化学反应器网络自动生成方法[J]. 清华大学学报(自然科学版), 2023, 63(4): 612-622.
GAO Qiaodong, LEI Fulin, ZHANG Zhedian. Automatic generation method of a chemical reactor network for predicting NOx emissions[J]. Journal of Tsinghua University (Science and Technology), 2023, 63(4): 612-622.
[14]
ZUBRILIN I A, GURAKOV N I, SEMENIKHIN A S, et al. Simulation of CO emission in primary and secondary zone of a small gas turbine combustion chamber using CFD and reactors network[C]. ASME 2019 Gas Turbine India Conference. Chennai, Tamil Nadu: ASME, 2019.
[15]
张文瀚, 王国峰, 赵巧男, 等. 基于CRN方法的空气分级燃烧室NOx排放研究[J]. 沈阳工程学院学报(自然科学版), 2020, 16(3): 29-33.
ZHANG Wenhan, WANG Guofeng, ZHAO Qiaonan, et al. Study on NOx emission of air staged combustion chamber based on CRN method[J]. Journal of Shenyang Institute of Engineering (National Science), 2020, 16(3): 29-33.
[16]
田园, 耿俊杰, 孙逸凡, 等. 天然气径向分级燃烧室低NOx排放的优化研究[J]. 清华大学学报(自然科学版), 2023, 63(4): 660-669.
TIAN Yuan, GENG Junjie, SUN Yifan, et al. Optimization investigation of low NOx emissions of natural gas radially staged combustor[J]. Journal of Tsinghua University (Science and Technology), 2023, 63(4): 660-669.
[17]
TURNS S R. An introduction to combustion: concepts and applications[M]. 2nd ed. New York: McGraw Hill Education, 2000: 111-143.
[18]
PARK J, NGUYEN T H, JOUNG D, et al. Prediction of NOx and CO emissions from an industrial lean-premixed gas turbine combustor using a chemical reactor network model[J]. Energy & Fuels, 2013, 27(3): 1643-1651.
[19]
耿俊杰, 田园, 孙逸凡, 等. 基于化学反应器网络方法的燃气轮机燃烧室NOx排放研究[J]. 中国电机工程学报, 2023, 43(12): 4657-4669.
GENG Junjie, TIAN Yuan, SUN Yifan, et al. Investigation on NOx emission characteristics of gas turbine combustor based on chemical reactor network method[J]. Proceedings of the CSEE, 2023, 43(12): 4657-4669.
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doi: 10.19666/j.rlfd.202411240
  • 接收时间:2024-11-28
  • 首发时间:2026-03-05
  • 出版时间:2025-09-25
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  • 收稿日期:2024-11-28
基金
National Science and Technology Major Project(Y2019-I-0022-0021)
国家科技重大专项(Y2019-I-0022-0021)
作者信息
    1.中国科学院先进能源动力重点实验室(工程热物理研究所),北京 100190
    2.中国科学院大学工程科学学院,北京 100049

通讯作者:

雷福林(1975),男,博士,研究员,主要研究方向为燃烧学、煤气化、多相流等,
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2种不同金属材料的力学参数

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Percentage of
total species (%)

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Number of
species
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Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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